Abstract
Due to their particular physiographic, geomorphic, soil cover, and complex surface-subsurface hydrologic conditions, karst regions produce distinct land–atmosphere interactions. It has been found that floods and droughts over karst regions can be more pronounced than those in non-karst regions following a given rainfall event. Five convective weather events are simulated using the Weather Research and Forecasting model to explore the potential impacts of land-surface conditions on weather simulations over karst regions. Since no existing weather or climate model has the ability to represent karst landscapes, simulation experiments in this exploratory study consist of a control (default land-cover/soil types) and three land-surface conditions, including barren ground, forest, and sandy soils over the karst areas, which mimic certain karst characteristics. Results from sensitivity experiments are compared with the control simulation, as well as with the National Centers for Environmental Prediction multi-sensor precipitation analysis Stage-IV data, and near-surface atmospheric observations. Mesoscale features of surface energy partition, surface water and energy exchange, the resulting surface-air temperature and humidity, and low-level instability and convective energy are analyzed to investigate the potential land-surface impact on weather over karst regions. We conclude that: (1) barren ground used over karst regions has a pronounced effect on the overall simulation of precipitation. Barren ground provides the overall lowest root-mean-square errors and bias scores in precipitation over the peak-rain periods. Contingency table-based equitable threat and frequency bias scores suggest that the barren and forest experiments are more successful in simulating light to moderate rainfall. Variables dependent on local surface conditions show stronger contrasts between karst and non-karst regions than variables dominated by large-scale synoptic systems; (2) significant sensitivity responses are found over the karst regions, including pronounced warming and cooling effects on the near-surface atmosphere from barren and forested land cover, respectively; (3) the barren ground in the karst regions provides conditions favourable for convective development under certain conditions. Therefore, it is suggested that karst and non-karst landscapes should be distinguished, and their physical processes should be considered for future model development.
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References
Angevine WM, Bazile E, Legain D, Pino D (2014) Land surface spinup for episodic modeling. Atmos Chem Phys 14(15):8165–8172
Best M, Grimmond CSB (2014) Importance of initial state and atmospheric conditions for urban land surface models’ performance. Urban Clim 10:387–406. doi:10.1016/j.uclim.2013.10.006
Bonacci O, Pipan T, Culver DC (2009) A framework for karst ecohydrology. Environ Geol 56:891–900
Bonan GB (2008) Forests and climate change: forcings, feedbacks, and the climate benefits of forests. Science 320(5882):1444–1449
Case JL, Crosson WL, Kumar SV, Lapenta WM, Peters-Lidard CD (2008) Impacts of high-resolution land surface initialization on regional sensible weather forecasts from the WRF model. J Hydrometeorol 9(6):1249–1266
Chen F, Dudhia J (2001) Coupling an advanced land surface–hydrology model with the Penn State–NCAR MM5 modeling system. Part I: model implementation and sensitivity. Mon Weather Rev 129:569–585
Chen F, Manning KW, LeMone MA, Trier SB, Alfieri JG, Roberts R, Tewari M, Niyogi D, Horst TW, Oncley SP, Basara JB (2007) Description and evaluation of the characteristics of the NCAR high-resolution land data assimilation system. J Appl Meteorol Climatol 46(6):694–713
Chou MD, Suarez MJ, Ho CH, Yan MMH, Lee KT (1998) Parameterizations for cloud overlapping and shortwave single-scattering properties for use in general circulation and cloud ensemble models. J Clim 11:202–214
Clark CA, Arritt RW (1995) Numerical simulations of the effect of soil moisture and vegetation cover on the development of deep convection. J Appl Meteorol 34:2029–2045
Collow TW, Robock A, Wu W (2014) Influences of soil moisture and vegetation on convective precipitation forecasts over the United States Great Plains. J Geophys Res Atmos 119:9338–9358. doi:10.1029/2014JD021454
Cosgrove BA, Lohmann D, Mitchell KE, Houser PR, Wood EF, Schaake JC, Robock A, Marshall C, Sheffield J, Duan Q, Luo L (2003) Real-time and retrospective forcing in the North American Land Data Assimilation System (NLDAS) project. J Geophys Res Atmos 108(D22):GCP3-1
Crowther J (1987) Ecological observations in tropical karst terrain, West Malaysia. III. Dynamics of the vegetation-soil-bedrock system. J Biogeogr 14:157–164
Dai Y, Dai Y, Zeng X, Dickinson RE, Baker I, Bonan GB, Bosilovich MG, Denning AS, Dirmeyer PA, Houser PR, Niu G, Oleson KW (2003) The common land model. Bull Am Meteorol Soc 84:1013–1023
Davies WE, Simpson JH, Ohlmacher GC, Kirk WE, Newton EG (1984) Digital engineering aspects of Karst Map. U.S. Geological Survey, National Atlas of the United States of America, GIS version by Tobin BD and Weary DJ. http://pubs.usgs.gov/of/2004/1352/
Durkee JD, Campbell L, Berry K, Jordan D, Goodrich G, Mahmood R, Foster S (2012) A synoptic perspective of the record 1–2 May 2010 mid-South heavy precipitation event. Bull Am Meteorol Soc 93(5):611–620
Fan X (2009) Impacts of soil heating condition on precipitation simulations in the Weather Research and Forecasting model. Mon Weather Rev 137:2263–2285
Ford D, Williams PD (2007) Karst hydrogeology and geomorphology. Wiley, New York, 576 pp
Fry J, Xian G, Jin S, Dewitz J, Homer C, Yang L, Barnes C, Herold N, Wickham J (2011) Completion of the 2006 national land cover database for the conterminous United States. PE & RS 77(9):858–864. http://www.mrlc.gov/nlcd2006.php
Gaines M (2012) Application of the weather research and forecasting (WRF) model to simulate a squall line: implications of choosing parameterization scheme combinations and model initialization data sets. Masters theses and specialist projects, paper 1181. http://digitalcommons.wku.edu/theses/1181
Gao J, Xue Y, Wu S (2013) Potential impacts on regional climate due to land degradation in the Guizhou Karst Plateau of China. Environ Res Lett 8(4):044037
Gonzalez GR, Verhoef A, Vidale PL, Braud I (2012) Incorporation of water vapor transfer in the JULES land surface model: implications for key soil variables and land surface fluxes. Water Resour Res 48:W05538. doi:10.1029/2011WR011811
Groves C (2007) Hydrological methods. In: Goldscheider N, Drew D (eds) Methods in karst hydrology. Taylor & Francis, London, pp 45–64
Groves C, Meiman J (2005) Weathering, geomorphic work, and karst landscape evolution in the Cave City groundwater basin, Mammoth Cave, Kentucky. Geomorphology 67:115–126
Groves C, Bolster C, Meiman J (2005) Spatial and temporal variations in epikarst storage and flow in south central Kentucky’s Pennyroyal Plateau sinkhole plain. US Geol Surv Sci Investig Rep 2005–5160:64–73
Hartmann A, Barbera JA, Lange J, Andreo B, Weiler M (2013) Progress in the hydrologic simulation of time variant recharge areas of karst systems—exemplified at a karst spring in Southern Spain. Adv Water Resour 54:149–160
Heilman JL, McInnes KJ, Kjelgaard JF, Owens MK, Schwinning S (2009) Energy balance and water use in a subtropical karst woodland on the Edwards Plateau, Texas. J Hydrol 373:426–435
Hess JW, White WB (1989) Chemical hydrology. In: White WB, White EL (eds) Karst hydrology: concepts from the Mammoth Cave area. Van Nostrand Reinhold, New York, pp 145–174
Jackson RB, Moore LA, Hoffmann W, Pockman WT, Linder CR (1999) Ecosystem rooting depth determined with caves and DNA. Proc Natl Acad Sci 96(20):11387–92
Ji Y, Zhou G, Wang S, Wang L (2015) Increase in flood and drought disasters during 1500–2000 in Southwest China. Nat Hazards 77(3):1853–1861
Jiang Z, Yuan D (1999) \(\text{ CO }_{2}\) source-sink in karst processes in karst areas of China. Episodes 22(1):33–35
Kain J, Fritsch M (1993) Convective parameterization for mesoscale models: the Kain–Fritsch scheme. In: The representation of cumulus convection in numerical models. Meteorological monographs. American Meteor Society, vol 24, no 46, pp 165–170
Lawston PM, Santanello JA Jr, Zaitchik BF, Rodell M (2015) Impact of irrigation methods on land surface model spinup and initialization of WRF forecasts. J Hydrometeorol 16(3):1135–1154
Leeper R, Mahmood R, Quintanar AI (2011) Influence of karst landscape on planetary boundary layer atmosphere: a Weather Research and Forecasting (WRF) model-based comparison. J Hydrometeorol 12:1512–1529
Li E, Jiang Z, Cao J, Jiang G, Deng Y (2003) The comparison of properties of karst soil and karst erosion ratio under different successional stages of karst vegetation in Nongla, Guangxi. Acta Ecol Sin 24(6):1131–1139
Lin Y (2011) GCIP/EOP surface: precipitation NCEP/EMC 4KM gridded data (GRIB) stage IV data. Version 1.0. UCAR/NCAR—Earth Observing Laboratory. http://data.eol.ucar.edu/dataset/21.093. Accessed 04 March 2017
Lin YL, Farley RD, Orville HD (1983) Bulk parameterization of the snow field in a cloud model. J Clim Appl Meteorol 22:1065–1092
McPherson RA (2007) A review of vegetation-atmosphere interactions and their influences on mesoscale phenomena. Prog Phys Geogr 31:261–285
Meng H, Wang L (2010) Advance in karst hydrological model. Prog Geogr 11:006
Mesinger F et al (2006) North American regional reanalysis. Bull Am Meteorol Soc 87:343–360. doi:10.1175/BAMS-87-3-343
Mesinger F, Janjic ZI (1974) Noise due to time-dependent boundary conditions in limited area models. GARP Programme Numer Exp Rep 4:31–32
Milanovic PT (1981) Karst hydrology. Water Resources Publications, Highlands Ranch, 434 pp
Mitchell K (2005) The community Noah land surface model (LSM)—user’s guide public release version 2.7.1. ftp://ftp.emc.ncep.noaa.gov/mmb/gcp/ldas/noahlsm/ver_2.7.1. Last visited 12 Sept 2014
Mlawer EJ, Taubman SJ, Brwon PD, Iacono MJ, Clough SA (1997) Radiative transfer for inhomogeneous atmosphere; RRTM, a validated correlated-k model for the longwave. J Geophys Res 102(D14):16 663–16 682
Moser BK, Stevens GR, Watts CL (1989) The two-sample \(t\)-test versus Satterwaite’s approximate \(F\) test. Commun Stat Theory Methodol 18:3963–75
Oke TR (1987) Boundary layer climates, 2nd edn. Routledge, London, pp 110–157
Palmer AN (2007) Cave geology. Cave Books, Dayton, 454 pp
Petty GW (2008) A first course in atmospheric thermodynamics. Sundog Publishing, Madison, 337 pp
Pielke RA (2001) Influence of the spatial distribution of vegetation and soils on the prediction of cumulus convective rainfall. Rev Geophys 39(2):151–177
Quintanar AI, Mahmood R (2012) Ensemble forecast spread induced by soil moisture changes over mid-south and neighbouring mid-western region of the USA. Tellus A Dyn Meteorol Oceanogr 64:17156. doi:10.3402/tellusa.v64i0.17156
Quintanar AI, Mahmood R, Loughrin J, Lovanh NC (2008) A coupled MM5-Noah land surface model-based assessment of sensitivity of planetary boundary later variables to anomalous soil moisture conditions. Phys Geogr 29:54–78. doi:10.2747/0272-3646.29.1.54
Quintanar AI, Mahmood R, Motley MV, Yan J, Loughrin J, Lovanh N (2009) Simulation of boundary layer trajectory dispersion sensitivity to soil moisture conditions: MM5 and Noah-based investigation. Atmos Environ 43:3774–3785
Rodell M, Houser PR, Berg AA, Famigliett JS (2005) Evaluation of 10 methods for initializing a land surface model. J Hydrometeorol 6(2):146–155
Ruxton GD (2006) The unequal variance \(t\)-test is an underused alternative to Student’s \(t\)-test and the Mann–Whitney \(U\) test. Behav Ecol 17(4):688–690. doi:10.1093/beheco/ark016
Santanello JA Jr, Kumar SV, Peters-Lidard CD, Harrison K, Zhou S (2013) Impact of land model calibration on coupled land-atmosphere prediction. J Hydrometeorol 14(5):1373–1400
Schwinning S (2008) The water relations of two evergreen tree species in a karst savanna. Oecologia 158(3):373–83
Skamarock WC, Klemp JB, Dudhia J, Gill DO, Barker DM, Duda MG, Huang XY, Wang W, Powers JG (2008) A description of the advanced research WRF version 3. NCAR tech note, NCAR/TN-475+STR
Suarez A, Mahmood R, Quintanar AI, Beltran-Przekurat A, Pielke RA Sr (2014) A comparison of the MM5 and the Regional Atmospheric Modeling System simulations for land–atmosphere interactions under varying soil moisture. Tellus A Dyn Meteorol Oceanogr 66:21486. doi:10.3402/tellusa.v66.21486
Weary DJ, Doctor DH (2014) Karst in the United States: a digital map compilation and database. US geological survey open-file report, pp 2014–1156
White WB (1988) Geomorphology and hydrology of karst terrains. Oxford University Press, New York, 480 pp
White WB, Culver DC, Herman JS, Kane TC, Mylroie JE (1995) Karst lands. Am Sci 83:450–459
Wilks DS (2010) Statistical methods in the atmospheric sciences, 3rd edn. Academic Press, New York, 676 pp
Winchester J, Mahmood R, Rodgers W, Hossain F, Rappin E, Durkee J, Chronis T (2017) A model-based assessment of potential impacts of man-made reservoirs on precipitation. Earth Interact 21:1–31
Xue Y, Sellers PJ, Kinter JL, Shukla J (1991) A simplified biosphere model for global climate studies. J Clim 4:345–64
Zhang Q, Xu CY, Zhang Z, Chen X, Han Z (2010) Precipitation extremes in a karst region: a case study in the Guizhou province, southwest China. Theor Appl Climatol 101:53–65. doi:10.1007/s00704-009-0203-0
Acknowledgements
The detailed information of datasets used is provided in Sect. 2. The digital karst maps incorporated into the WRF model were obtained from USGS at http://pubs.usgs.gov/of/2004/1352/. The 2006 National Land Cover Data were obtained from the USGS at http://www.mrlc.gov/nlcd2006.php. The North American Regional Reanalysis data provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, were obtained from http://www.esrl.noaa.gov/psd/. The NCEP Stage-IV precipitation data for model evaluation were obtained from the NCAR/UCAR Earth Observing Laboratory at http://data.eol.ucar.edu/codiac/dss/id=21.093. This research was funded by the Kentucky Climate Center and supported by the Western Kentucky University Interdisciplinary Research and Creative Activity grant and the Faculty Undergraduate Student Engagement grant. Support was also provided in part from a USDA-ARS Grant #58-6445-6-068. The authors thank Dr. Joshua Durkee for valuable discussions and William Rodgers for technical assistance. We also thank Ryan Difani, Tyler Binkley, Allie Durham, and Andrew Schuler for their initial involvement in a related atmospheric modelling class project.
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Johnson, C.M., Fan, X., Mahmood, R. et al. Evaluating Weather Research and Forecasting Model Sensitivity to Land and Soil Conditions Representative of Karst Landscapes. Boundary-Layer Meteorol 166, 503–530 (2018). https://doi.org/10.1007/s10546-017-0312-8
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DOI: https://doi.org/10.1007/s10546-017-0312-8
Keywords
- Barren land cover
- Karst landscapes
- Model precipitation events
- Model sensitivity
- Weather Research and Forecasting model